Probabilities, Random Variables, and Random Processes: Digital and Analog |
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Page 48
... formula is also used as the definition of two independent events . Using set theory , the concepts of conditional probabilities and depen- dent and independent events may be extended to three or more events . It should follow clearly ...
... formula is also used as the definition of two independent events . Using set theory , the concepts of conditional probabilities and depen- dent and independent events may be extended to three or more events . It should follow clearly ...
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... formula P ( A / B ) = NAB / Ng to find the following probabili- ties : ( a ) A computer word of 8 bits contains three zeros given that the first bit is a 1 . ( b ) A computer word of 8 bits contains two consecutive zeros given that it ...
... formula P ( A / B ) = NAB / Ng to find the following probabili- ties : ( a ) A computer word of 8 bits contains three zeros given that the first bit is a 1 . ( b ) A computer word of 8 bits contains two consecutive zeros given that it ...
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Digital and Analog Michael O'Flynn. 2. Redo Problem 1 using the formula P ( A / B ) = P ( ANB ) P ( B ) 3. Use the formula P ( A , A2 A , ) = N P ( A1 ) P ( A2 / A1 ) · · P ( A / A12A ) to find the probability that 5 cards dealt n from a ...
Digital and Analog Michael O'Flynn. 2. Redo Problem 1 using the formula P ( A / B ) = P ( ANB ) P ( B ) 3. Use the formula P ( A , A2 A , ) = N P ( A1 ) P ( A2 / A1 ) · · P ( A / A12A ) to find the probability that 5 cards dealt n from a ...
Contents
1 | 3 |
5 | 54 |
General Formulation and Solution of Problems | 69 |
Copyright | |
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Common terms and phrases
A₁ autocorrelation function average axiom B₁ balls Chapter convolution correlation integrals cross-correlation cross-correlation function cumulative distribution function dadß defined definition delta function denoted derivation deterministic discrete Fourier transform discrete probability theory discrete random process DRILL SET ensemble ergodic evaluate event space Example finite first-order stationary formula fundamental theorem fxy(a fy(B fz(y given impulse response joint density function joint mass function Laplace transform linear system M₁ member waveform notation obtained otherwise output periodic function periodic waveform permutations plotted in Figure points power spectral density probability measure probability theory problem properties pulse px(a random input random phenomenon range Rxx(T sample description space sampled values second-order stationary set theory shown in Figure shown plotted signal sketch SOLUTION solved statistics Sxx(w Ticket Pays two-sided Laplace transform two-sided z transform typical member X₁ z transform zero-mean